An Analysis Method of Factors Influencing Prediction of Carbon Dioxide Concentration at Arbitrary Time and Space

Abstract

The invention provides an analysis method for predicting influencing factors of carbon dioxide concentration at any time and space position. Firstly, the sparse and uneven satellite carbon dioxide column concentration observation data and corresponding environmental factors, including land cover factors, climate meteorological factors and combustion emission factors, are combined. The XGBoost algorithm constructs a model for simulating the temporal and spatial distribution of carbon dioxide in the region, and extracts the temporal and spatial distribution trend variables of carbon dioxide; then, using the regional carbon dioxide temporal and spatial distribution model constructed above, combined with the global sensitivity analysis algorithm, the quantitative evaluation of the sensitivity of environmental factors is realized. Quantitatively determine the influence degree and size of various environmental factors that affect the temporal and spatial distribution of carbon dioxide in the region based on the results of the sex analysis. Compared with the traditional method, the method of the invention can simulate the regional carbon dioxide concentration distribution with higher precision, and realize the quantitative evaluation of the importance degree of environmental variables.

Description

technical field [0001] The invention relates to the field of remote sensing greenhouse gas monitoring, in particular to a machine learning-based method for simulating the temporal and spatial distribution of atmospheric carbon dioxide and a global sensitivity analysis method for influencing factors. Background technique [0002] Carbon dioxide is the most important greenhouse gas and the biggest contributor to global warming. Accurately understanding the temporal and spatial distribution of carbon dioxide concentration and its changing trend is very important for understanding and mitigating the greenhouse effect. Satellite observations can accurately provide ground-level carbon dioxide information with a certain temporal and spatial resolution and relatively long time-series observations. However, due to the influence of clouds and aerosols, there are vacancies in satellite observation data in practical applications, and it is difficult to accurately analyze the spatial and ...

AI Technical Summary

Problems solved by technology

The influencing factors are complex and the process is complicated, and there are many related studies

However, most of them are qualitative analysis or correlation analysis between environmental factors and carbon dioxide concentration, and there are few quantitative evaluation methods for the degree of influence of multiple factors, and it is impossible to realize quantitative analysis of the contribution and impact of different environmental factors on atmospheric carbon dioxide concentration.

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